The Base Model Is Dead — Varun Singh, Arcee AI
Varun Singh from Arcee AI argues that the traditional view of base models—as mirrors of the internet upon which other techniques build—no longer holds true.
Modern models integrate instruction data and synthetic training data much earlier in the process, and a new intermediate stage has emerged. Raw webtext takes a backseat while reinforcement learning (a method to train AI to reason better) has become so important that it changes what the base model needs to do from the start. Singh discusses practical challenges his team encountered when training the Trinity series, such as achieving the right balance across different data sources and achieving model stability early so it is prepared for what comes later. The point is that the base model's role is constantly being redefined as capacity increases.
Vibekollen prepared this summary with AI from the original publication. The content belongs to AI Engineer.
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